scholarly journals Do the methods used to analyse missing data really matter? An examination of data from an observational study of Intermediate Care patients

2012 ◽  
Vol 5 (1) ◽  
Author(s):  
Billingsley Kaambwa ◽  
Stirling Bryan ◽  
Lucinda Billingham
Keyword(s):  
Missing Data ◽  
Observational Study ◽  
Intermediate Care

Unplanned Transfers From Intermediate Care Units to Intensive Care Units: A Cohort Study

2021 ◽  
Vol 30 (5) ◽  
pp. 397-400
Author(s):  
Joao Gabriel Rosa Ramos ◽  
Gabriel Machado Naus dos Santos ◽  
Marina Chetto Coutinho Bispo ◽  
Renata Cristina de Almeida Matos ◽  
Gil Mario Lopes Santos de Carvalho ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Cohort Study ◽  
Intensive Care ◽  
Observational Study ◽  
Hospital Mortality ◽  
Odds Ratio ◽  
Intermediate Care ◽  
Icu Mortality ◽  
Patient Transfers ◽  
Reason For Admission

This study evaluated unplanned transfers from the intermediate care unit (IMCU) to the intensive care unit (ICU) among urgent admissions. This retrospective, observational study was conducted in 2 ICUs and 1 IMCU. Three patterns of urgent admission were assessed: admissions to the ICU only, admissions to the IMCU only, and admissions to the IMCU with subsequent transfer to the ICU. Of 5296 admissions analyzed, 1396 patients (26.4%) were initially admitted to the IMCU. Of these, 172 (12.3%) were transferred from the IMCU to the ICU. Mortality was higher in patients transferred from the IMCU to the ICU than in the 3900 ICU-only patients (odds ratio, 3.22; 95% CI, 1.52-6.80). Most transfers from the IMCU to the ICU (135; 78.5%) were due to deterioration of the condition for which the patient was admitted. Patient transfers from the IMCU to the ICU were common, were associated with increased hospital mortality, and were mostly due to deterioration in the condition that was the reason for admission.

scholarly journals Identifying patterns of item missing survey data using latent groups: an observational study

BMJ Open ◽  
2017 ◽  
Vol 7 (10) ◽  
pp. e017284 ◽  
Author(s):  
Adrian G Barnett ◽  
Paul McElwee ◽  
Andrea Nathan ◽  
Nicola W Burton ◽  
Gavin Turrell
Keyword(s):  
Logistic Regression ◽  
Missing Data ◽  
Observational Study ◽  
Latent Class ◽  
Survey Design ◽  
Latent Class Model ◽  
Information Criterion ◽  
Sleep Time ◽  
Class Model ◽  
Number Of Classes

ObjectivesTo examine whether respondents to a survey of health and physical activity and potential determinants could be grouped according to the questions they missed, known as ‘item missing’.DesignObservational study of longitudinal data.SettingResidents of Brisbane, Australia.Participants6901 people aged 40–65 years in 2007.Materials and methodsWe used a latent class model with a mixture of multinomial distributions and chose the number of classes using the Bayesian information criterion. We used logistic regression to examine if participants’ characteristics were associated with their modal latent class. We used logistic regression to examine whether the amount of item missing in a survey predicted wave missing in the following survey.ResultsFour per cent of participants missed almost one-fifth of the questions, and this group missed more questions in the middle of the survey. Eighty-three per cent of participants completed almost every question, but had a relatively high missing probability for a question on sleep time, a question which had an inconsistent presentation compared with the rest of the survey. Participants who completed almost every question were generally younger and more educated. Participants who completed more questions were less likely to miss the next longitudinal wave.ConclusionsExamining patterns in item missing data has improved our understanding of how missing data were generated and has informed future survey design to help reduce missing data.

scholarly journals Predictors of missing data in injury surveillance: an observational study

2012 ◽  
Vol 18 (Suppl 1) ◽  
pp. A237.1-A237
Author(s):  
G O'Reilly ◽  
P Cameron ◽  
D Jolley
Keyword(s):  
Missing Data ◽  
Observational Study ◽  
Injury Surveillance

An observational study of missing data inquiry from randomized trial authors showed a poor response

2020 ◽  
Vol 119 ◽  
pp. 19-25
Author(s):  
Sofia Tsokani ◽  
Dimitrios Mavridis ◽  
Shahab Hajibandeh ◽  
Shahin Hajibandeh ◽  
George A. Antoniou ◽  
...  
Keyword(s):  
Missing Data ◽  
Observational Study ◽  
Randomized Trial ◽  
Poor Response ◽  
Data Inquiry

scholarly journals High-flow oxygen therapy through nasal cannula: Prospective observational study in an intermediate care unit

2016 ◽  
Vol 22 (5) ◽  
pp. 292-293
Author(s):  
P. Demelo-Rodríguez ◽  
M. Olmedo Samperio ◽  
D.G. Gaitán Tocora ◽  
J.C. Cano Ballesteros ◽  
J. del Toro Cervera ◽  
...  
Keyword(s):  
Observational Study ◽  
Oxygen Therapy ◽  
Prospective Observational Study ◽  
High Flow ◽  
Nasal Cannula ◽  
Intermediate Care ◽  
Intermediate Care Unit ◽  
High Flow Oxygen

scholarly journals Efficacy of an implementation package on documentation of central venous catheter insertions: an observational study

2021 ◽  
Vol 10 (2) ◽  
pp. e001155
Author(s):  
Erik Linné ◽  
Maria Adrian ◽  
Peter Bentzer ◽  
Thomas Kander
Keyword(s):  
Missing Data ◽  
Central Venous Catheter ◽  
Observational Study ◽  
Electronic Health Record ◽  
Venous Catheter ◽  
Study Data ◽  
Health Record ◽  
Central Venous ◽  
Electronic Health ◽  
Implementation Package

BackgroundProper documentation of central venous catheter (CVC) insertions in electronic healthcare records is the basis for good follow-up and quality assurance. We have noted serious deficiencies in the documentation of CVC insertions and introduced an implementation package with the purpose of increasing the completeness of this documentation. The aim of the present study was to estimate the effect of the implementation package by assessing the proportion of missing data before and after the introduction of the implementation package.MethodsIn this single centre observational study, data from CVC insertion templates in a common electronic health record were extracted and analysed after introducing the implementation package. The package included adoption of new local CVC-directions, a new updated CVC-insertion template in the regional common electronic health record and a review of all CVC-insertion templates with a reminder to the inserting physician to supplement missing data. The proportion of terms with missing data was reviewed and also compared with the proportion of missing data in a study prior to the introduction of the package.ResultsIn total, 7126 CVC-insertion templates were included. Of these 5539 (78%) were without missing data for any of the 13 predefined variables. Completed insertion templates for three common terms increased from 38% prior to the introduction of the implementation package to 93%, which represents an absolute reduction for missing data of 55% (95% CI 53% to 56%, p<0.0001).ConclusionThe implementation package was highly effective in increasing the proportion of fully documented CVC insertions.

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